Artifical neural networks height-weight problem

i plan to use neurodotnet for my phd thesis, but before that i just want to build some small solutions to get used to the dll structure. the first problem that i want to model using backward propagation is height-weight ratio. I have some height and weight data, i want to train my NN so that if i put in some weight then i should get correct height as a output. i have 1 input 1 hidden and 1 output layer. Now here is first of many things i cant get around :) 1. my height data is in form of 1.422, 1.5422 ... etc and the corresponding weight data is 90 95, but the NN takes the input as 0/1 or -1/1 and given the output in the same r开发者_JS百科ange. how to address this problem

You have to normalize the data. If you don't know what the ranges for the real-world inputs will be then pick a sensible range that will cover all reasonable inputs. If the NN never sees inputs <0.1 and >0.9 I don't think it will be a problem.